[BioC] grouping samples from distinct runs in limma

[Edmund Chang]

Dear list,
I am working with Affymetrix microarrays and looking for differential 
gene expression using limma.  We repeated the same microarray experiment 
two separate times (about a year apart), because *some* of the 
microarrays came out bad.  So instead of running the same samples again 
(technical replicates), we generated an entirely new set of RNA.
(i.e. for treatment A:  1st run- A1, A2, A3;  2nd run- a1, a2, a3)
(and for treatment B: 1st run- B1,B2,B3; 2nd run- b1,b2,b3)

I was wondering how to handle this sort of data in limma.  Because they 
are biologically distinct, I am tempted to group them together (e.g. 
combining samples A1,A2,A3 and a1, a2, a3 into A1-A6).  But I have 
reservations about grouping arrays which were run one year apart from 
each other.

How can I prove to myself that samples which were identically treated 
but came from separate experiments can be grouped together in limma? Do 
I calculate the correlation coefficient between groups 
(corfit$consensus) and use that to determine if the groups are closely 
correlated?

or is there another function in limma that can handle this scenario?

Any input will be highly appreciated!
Edmund Chang